基于机动弹道SAR高阶运动参数估计的地动目标成像

IF 8.6 1区 地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yifan Wang;Shiyang Tang;Linrang Zhang;Chenghao Jiang;Zixuan He;Jiahao Han;Zhanye Chen;Hongmeng Chen;Daobao Xu
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引用次数: 0

摘要

机动为高斜视合成孔径雷达(SAR)提供了灵活性,也意味着复杂的回波信号特性,特别是地面运动目标成像(GMTIm)。分析了机动平台与运动目标参数之间的相互作用。分析认为,定位时应考虑三个关键因素:方位角频谱混叠、多普勒质心模糊和高阶误差。为了应对这些挑战,提出了一种机动平台GMTIm方法。该方法采用了一种基于扩展广义高阶模糊函数(EGHAF)的先进参数估计方法,通过二维扩展,可以在低信噪比条件下同时估计所有阶的高阶相位系数。由于传统方法对高阶相位的估计和补偿通常被忽略,因此该方法更适合于具有机动平台的运动目标成像。仿真和实际数据结果验证了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ground-Moving Target Imaging Based on High-Order Motion Parameter Estimation for SAR With Maneuvering Trajectory
Maneuver provides flexibility for highly squinted synthetic aperture radar (SAR) and also means complicated signal characteristics in the echo, especially for ground moving target imaging (GMTIm). This article analyzes the interaction of parameters between the maneuvering platform and the moving target. The analysis suggests that three key factors should be taken into account: azimuth spectrum aliasing, Doppler centroid ambiguity, and high-order errors. To deal with these challenges, a novel GMTIm methodology for maneuvering platform is presented. The proposed approach employs an advanced parameter estimation method based on the extended generalized high-order ambiguity function (EGHAF), which enables simultaneous estimation of high-order phase coefficients across all orders in low signal-to-noise ratio (SNR) conditions through 2-D extension. Due to the estimation and compensation for higher order phases, which are usually ignored in conventional methods, the proposed method is more suitable for moving target imaging with maneuvering platforms. The superiority of the proposed approach is verified by simulation and real data results.
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来源期刊
IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing 工程技术-地球化学与地球物理
CiteScore
11.50
自引率
28.00%
发文量
1912
审稿时长
4.0 months
期刊介绍: IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.
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